Biomarcadores de oclusiones venosas retinianas mediante estrategia de aprendizaje profundo aplicada en imágenes adquiridas por OCT angiografía

dc.contributor.advisorQuijano Nieto, Bernardo Alfonso
dc.contributor.authorGallego Suárez, Laura Juliana
dc.contributor.educationalvalidatorPerdomo Charry Oscar Julian
dc.contributor.orcid0000-0001-5056-5956spa
dc.date.accessioned2023-02-07T19:37:18Z
dc.date.available2023-02-07T19:37:18Z
dc.date.issued2023-02
dc.descriptionilustraciones, fotografíasspa
dc.description.abstractPropósito: Desarrollar un método computacional basado en Deep Learning (DL) para detectar automáticamente biomarcadores de oclusiones de venas retinianas en imágenes adquiridas por angiografía por tomografía de coherencia óptica (OCT-A) Diseño: Desarrollo de algoritmo para detectar biomarcadores de oclusiones de venas retinianas utilizando datos retrospectivos. (Texto tomado de la fuente)spa
dc.description.abstractPurpose: To develop a computational method based on Deep Learning (DL) to automatically detect biomarkers of retinal vein occlusions in images acquired by optical coherence tomography angiography (OCT- A) Design: Algorithm development for detect biomarkers of retinal vein occlusions using retrospective data. Participants: Images of the superficial, deep, en face, choriocapillaris and outer retina to choriocapillaris (ORCC) layers obtained from 254 patients attended in an Ophthalmology Clinic were used to train and test an artificial intelligence (AI) model. Methods: The OCT-A scans were manually annotated with four biomarkers (BMs): disruption of the perifoveal capillary plexus, non-perfusion areas (NPAs), vascular tortuosity and cystoid spaces. Segmentation and identification were subsequently provided to build and training the DL model using Deep Convolutional Neural Networks (DNN) Main Outcome Measures: detection rate and jaccard index Results: The detection rate of the model for disruption of the perifoveal capillary plexus, non-perfusion areas (NPAs), vascular tortuosity and cystoid spaces were 93%, 92%, 91% and 84% respectively. The Jaccard index values were 0.85, 0.77, 0.72 and 0.73 respectively Conclusion: The proposed DL model may ideng
dc.description.degreelevelEspecialidades Médicasspa
dc.description.degreenameEspecialista en Oftalmologíaspa
dc.format.extentxiii, 37 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/83367
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Medicinaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Medicina - Especialidad en Oftalmologíaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddcmedicinaspa
dc.subject.lembBiochemical markerseng
dc.subject.lembMarcadores bioquímicosspa
dc.subject.lembEye diseaseseng
dc.subject.lembEnfermedades de los ojosspa
dc.subject.proposalInteligenciaspa
dc.subject.proposalArtificialspa
dc.subject.proposalOclusiónspa
dc.subject.proposalVenosaspa
dc.subject.proposalTomografiaspa
dc.subject.proposalCoherenciaspa
dc.subject.proposalOpticaspa
dc.titleBiomarcadores de oclusiones venosas retinianas mediante estrategia de aprendizaje profundo aplicada en imágenes adquiridas por OCT angiografíaspa
dc.title.translatedBiomarkers of retinal vein occlusions using a deep learning strategy applied to images obtained by OCT angiography.eng
dc.typeTrabajo de grado - Especialidad Médicaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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